Physical activity is a known protective factor against depression but physical activity competes with other time-consuming behaviors that may increase depression risk. This study investigates the association between time spent in various movement-related activities and incident major depression, with a particular focus on the effects of replacing TV-watching time with other activities. Additionally, we explored whether the impact of substituting TV-watching differs across age groups.

A population-based cohort study (Lifelines) with four-year follow-up, including 65,454 non-depressed adults (18+). Participants self-reported time spent in active commuting, leisure, sports, household, work or school physical-related activities, TV-watching, and sleep. Major depressive disorder was assessed using the Mini International Neuropsychiatric Interview. Compositional isotemporal data analysis was performed to analyze the effect of reallocating time in TV-watching with other activities adjusting for potential confounders. Interactions with age groups were also examined.

The incidence of major depressive disorder was 2.4%. Reallocating TV-watching time to any other physical activity or sleep reduced this risk in middle-aged adults. In older adults, only substituting TV-watching time with sports reduced the probability of becoming depressed. No significant reduction in probabilities for incident depression was found in younger adults.

Replacing TV-watching time with other activities, including sleep, may serve as a preventive strategy against depressive disorder in middle-aged adults, while only the substitution with sports seems beneficial for older adults. Future research should aim to identify other activities, particularly in younger adults, that may prevent depression.

Maternal alcohol consumption can adversely affect children’s development, but the impact of paternal drinking is less understood. We aimed to investigate whether maternal or paternal alcohol consumption during pregnancy affected children’s mental health and behavior.

A total of 2,013 parent–child triads from the European Longitudinal Study of Pregnancy and Childhood cohort were used. Data on alcohol consumption was obtained from questionnaires during pregnancy and after the child’s birth. Mental health and behavior of children were assessed with Strength and Difficulties Questionnaire (SDQ). The associations were tested using linear regression, adjusting for socio-demographic and psychosocial covariates.

Increased maternal alcohol consumption was associated with higher total SDQ scores at ages 7, 11, and 18 years old when the outcomes were reported by mothers, but only at 11 years when reported by children. We did not observe any dose–response relationship, and the effect size did not change during the follow-up. The effects were observed across various domains of SDQ: in the emotional symptoms subscale at age 11, in the conduct problems subscale at ages 7 and 11, and in the hyperactivity/inattention subscale at age 18. Paternal alcohol consumption was not associated with SDQ.

Maternal alcohol consumption during pregnancy is associated with long-term effects on children’s mental health and behavior, particularly when reported by mothers. No association was found between paternal alcohol consumption, suggesting that the results may stem from biological effects of alcohol or other factors beyond the direct exposure, potentially encompassing broader maternal psychosocial or behavioral characteristics.

Exposure to Adverse Childhood Experiences (ACEs) might increase the risk of suicide behaviors in the general adult population, while this association in individuals with affective disorders remains less characterized.

A comprehensive search was conducted in MEDLINE, PsycINFO, CINAHL, Web of Science, Scopus, and PubMed up to July 10th, 2024. Observational studies that compared the risk of suicide behaviors in individuals exposed and unexposed to ACEs were included. Pairwise random-effects meta-analyses were conducted, and the certainty of evidence was assessed with validated criteria.

A total of 41 studies from 17 countries, comprising 19,588 participants, were analyzed. The main findings indicated a significant association between ACEs and suicidal behaviors, with an odds ratio (OR) of 1.98 (95% confidence interval [CI] 1.74–2.26), and a “highly suggestive” strength of association. This was consistent across diagnostic subgroups (i.e., Major Depressive Disorders, Bipolar Disorders, and mixed diagnoses). The association was confirmed for any ACE, with sexual abuse being the most frequently reported and showing the highest risk (OR 2.24; 95% CI 1.90–2.64), for suicidal ideation (OR 2.16; 95% CI 1.42–3.29), and for suicide attempts (OR 1.95; 95% CI 1.70–2.25), while death by suicide and non-suicidal self-injury were underreported. Meta-regression analyses did not suggest potential moderators, though underreporting was noted.

This meta-analysis shows that exposure to ACEs nearly doubles the risk of suicide behaviors in individuals with affective disorders, warranting the targeted clinical, research, and policy measures to timely address this global mental health issue.

The neurobiological basis of suicidal behaviour remains poorly understood. However, emerging evidence suggests that inflammation and vascular homeostasis factors may play a role in its pathophysiology. Childhood trauma, through immune system dysfunction and increased risk of suicidal behaviours, might influence these associations. This study examined the relationships between immune-inflammatory and vascular homeostasis-related markers and their interaction with childhood trauma in relation to a history of suicide attempts in individuals with depression.

A total of 328 patients with major depression were recruited: 166 with a history of suicide attempts and 162 without. Using multivariate binary logistic regression models adjusted for cofounders, we examined the associations between childhood trauma, levels of platelet-related immune markers (serotonin, MCP-1, TSP-1, TSP-2, PDGF-AB, PDGF-BB), and suicide attempt history. Independent associations between PDGF-BB, childhood trauma, and suicide attempts were further assessed using interaction models. Stratified sensitivity analyses based on childhood trauma history were also conducted.

Childhood trauma consistently emerged as associated with suicide attempts across all models. Among the measured biomarkers, higher TSP-2 levels were associated with a suicide attempt history, independent of childhood trauma. Meanwhile, while PDGF-BB alone was not directly linked to suicide attempt history, the interaction analysis revealed that individuals with lower PDGF-BB levels and more severe childhood trauma were more likely to have attempted suicide.

TSP-2 and PDGF-BB are potential biomarkers linked to suicide attempts, with distinct roles in the interplay between biological processes and early-life adversity. These insights can inform the biomarker-informed development of tailored prevention and treatment strategies.

The use of coercive measures is an increasingly debated aspect of psychiatric treatment. Considering the multitude of negative effects, patients, clinicians, and ethicists alike have called for a more cautious application of coercion. It therefore remains important to investigate which organizational characteristics have the potential to facilitate efficient coercion reduction. The same holds true for the efficient reduction of symptom severity during inpatient treatment.

The current study compared 22 Swiss psychiatric clinics treating 45,095 cases regarding their relative efficiency in treating cases without coercion given their staff resources. To this end, we applied a Data Envelopment Analysis to clinical routine data. We focused specifically on inefficiencies attributable to management factors independent of the clinics’ total staff numbers. We further compared the clinics’ relative efficiencies regarding changes of self-reports and third-person reports of symptom severity during inpatient stays.

Efficiency scores suggest that on average, the clinics could improve the percentage of cases treated without coercion by 9% and the changes of symptom severity by 34% (for third-person ratings) or 18% (for self-reports) while keeping staff numbers constant. An analysis of specific coercion types revealed that the potential for efficiency improvements via management was highest for movement restrictions. We found no effect of clinic size on efficiency scores regarding any of the outcome measures.

Our results underline the importance of management factors beyond staff resources (e.g., staff trainings or changes in ward structure and treatment concepts) for the efficient reduction of coercion and psychiatric symptoms during inpatient stays.

Improving media adherence to World Health Organization (WHO) guidelines is crucial for preventing suicidal behaviors in the general population. However, there is currently no valid, rapid, and effective method to evaluate the adherence to these guidelines.

This comparative effectiveness study (January–August 2024) evaluated the ability of two artificial intelligence (AI) models (Claude Opus 3 and GPT-4O) to assess the adherence of media reports to WHO suicide-reporting guidelines. A total of 120 suicide-related articles (40 in English, 40 in Hebrew, and 40 in French) published within the past 5 years were sourced from prominent newspapers. Six trained human raters (two per language) independently evaluated articles based on a WHO guideline-based questionnaire addressing aspects, such as prominence, sensationalism, and prevention. The same articles were also processed using AI models. Intraclass correlation coefficients (ICCs) and Spearman correlations were calculated to assess agreement between human raters and AI models.

Overall adherence to WHO guidelines was ~50% across all languages. Both AI models demonstrated strong agreement with human raters, with GPT-4O showing the highest agreement (ICC = 0.793 [0.702; 0.855]). The combined evaluations of GPT-4O and Claude Opus 3 yielded the highest reliability (ICC = 0.812 [0.731; 0.869]).

AI models can replicate human judgment in evaluating media adherence to WHO guidelines. However, they have limitations and should be used alongside human oversight. These findings may suggest that AI tools have the potential to enhance and promote responsible reporting practices among journalists and, thus, may support suicide prevention efforts globally.

Heterogeneous symptoms in major depression contribute to unsuccessful antidepressant treatment, termed treatment-resistant depression (TRD). Psychometric network modeling conceptualizes depression as interplay of symptoms with potential benefits for treatment; however, a knowledge gap exists regarding networks in TRD.

Symptoms from 1,385 depressed patients, assessed by the Montgomery-Åsberg-depression rating scale (MADRS) as part of the “TRD-III” cohort of the multinational research consortium “Group for the Studies of Resistant Depression,” were used for Gaussian graphical network modeling. Networks were estimated for two timepoints, pretreatment and posttreatment, after the establishment of outcomes response, non-response, and TRD. Applying the network-comparison test, edge weights, and symptom centrality was assessed by bootstrapping. Applying the network-comparison test, outcome groups were compared cross-sectionally and longitudinally regarding the networks’ global strength, invariance, and centrality.

Pretreatment networks did not differ in global strength, but outcome groups showed distinct symptom connections. For both response and TRD, global strength was reduced posttreatment, leading to significant differences between each pair of networks posttreatment. Sadness, lassitude, inability-to-feel, and pessimistic thoughts ranked most centrally in unfavorable outcomes, while reduced-appetite and suicidal thoughts were more densely connected in response. Connections between central symptoms increased in strength following unsuccessful treatment, particularly regarding links involving pessimistic thoughts in TRD.

Treatment reduced global network strength across outcome groups. However, distinct symptom networks were found in patients showing response to treatment, non-response, and TRD. More easily targetable symptoms such as reduced-appetite were central to networks in patients with response, while pessimistic thoughts may be a key symptom upholding disease burden in TRD.

Nowadays, both researchers and clinicians alike have to deal with increasingly larger datasets, specifically also in the context of mental health data. Sophisticated tools for dataset visualization of information from various item-based instruments, such as questionnaire data or data from digital applications or clinical documentations, are still lacking, specifically for an integration at multiple levels and for use in both data organization and appropriate construction for its valid use in subsequent analyses.

Here, we introduce ItemComplex, a Python-based framework for ex-post visualization of large datasets. The method exploits the comprehensive recognition of instrument alignments and the identification of new content networks and graphs based on item similarities and shared versus differential conceptual bases within and across data and studies.

The ItemComplex framework was evaluated using four existing large datasets from four different cohort studies and demonstrated successful data visualization across multi-item instruments within and across studies. ItemComplex enables researchers and clinicians to navigate through big datasets reliably, informatively, and quickly. Moreover, it facilitates the extraction of new insights into construct representations and concept identifications within the data.

The ItemComplex app is an efficient tool in the field of big data management and analysis addressing the growing complexity of modern datasets to harness the potential hidden within these extensive collections of information. It is also easily adjustable for individual datasets and user preferences, both in the research and clinical field.

Due to limited inpatient care resources and high healthcare expenditures, understanding factors that affect lengths of stay (LOS) is highly relevant. We aimed to investigate associations between metabolic disturbances and LOS in a psychiatric hospital and to identify other clinical and sociodemographic LOS predictors.

Patients admitted to one of the units of the general psychiatric or psychogeriatric departments between January 1, 2007 and December 31, 2020, were included. Metabolic disturbances (i.e., the metabolic syndrome and its five components) were defined using the International Diabetes Federation definition. Cox frailty regression models with time-varying coefficients were used to investigate the association between metabolic disturbances and LOS. Hazard ratios (HR) >1 and HR < 1 indicated the relative likelihood of shorter and extended LOS, respectively.

A total of 7,771 patients for 16,959 hospital stays throughout 14 years of follow-up were included. Central obesity (HR = 0.82; 95% confidence interval [CI] = [0.76–0.89]), hyperglycemia (HR = 0.83; 95% CI = [0.78–0.89]), hypertriglyceridemia (HR = 0.87; 95% CI = [0.80–0.92]), and the metabolic syndrome (HR = 0.76; 95% CI = [0.70–0.82]) were associated with an increased risk of extended LOS in the psychiatric hospital, while underweight (HR = 1.30, 95% CI = [1.09–1.56]) and HDL hypocholesterolemia (HR = 1.10, 95% CI = [1.03–1.18]) were associated with a higher likelihood of shorter LOS. In first-episode psychosis patients, hypertriglyceridemia (HR = 0.82; 95% CI = [0.67–0.99]) and hypertension (HR = 0.76, 95% CI = [0.58–0.99]) were associated with extended LOS when considering all stays, while no association was found when considering the first stay per patient.

Future studies should determine whether better metabolic monitoring and treatment of metabolic disturbances can contribute to reducing LOS.

Recent meta-analyses support the inclusion of cognitive behavioral therapy (CBT) in schizophrenia treatment. Metacognitive Training (MCT) for psychosis is a psychoeducational program derived from CBT, with most meta-analyses showing favorable results. Although meta-analyses are commonly used in clinical practice to guide evidence-based decision-making, the grading system provides complementary results by offering a structured approach for assessing the strength and reliability of evidence and deriving grades of recommendations accordingly.

Our research applies the guidelines from the World Federation of Societies of Biological Psychiatry (WFSBP) to propose grades of recommendation for MCT for psychosis, analyzing 38 randomized controlled trials (RCTs) (n = 1942) and 10 meta-analyses. The primary outcome was positive symptoms, with secondary measures including negative symptoms, general psychopathology, self-esteem, functioning, insight, and cognitive function.

Our findings are primarily based on the risks of bias attributed to RCTs (11 high, 19 moderate, 6 low) and, when necessary, on the overall confidence attributed to meta-analyses (3 low, 7 critically low). According to the WFSBP guidelines, strong recommendations should be made for using MCT for psychosis to improve post-treatment positive symptoms, delusions, and total psychotic symptoms (WFSBP-grade 1). Limited recommendations (WFSBP-grade 2) could be made for using MCT to improve post-treatment visuospatial abilities and to maintain benefits over time in psychopathology, functioning, self-esteem, episodic memory, and attention.

MCT for psychosis is an evidence-based program, especially for positive symptoms, with long-lasting clinical benefits. These recommendations should be interpreted with caution given potential residual biases and heterogeneity among studies.

Neurodevelopmental conditions are crucial risk factors for catatonia in pediatric and adult populations. Recent case reports and studies have identified an increasing number of genetic abnormalities likely contributing to catatonia. Catatonia associated with genetic abnormalities is challenging in terms of identification, chronicity, and resistance to treatment. In addition, understanding these genetic abnormalities through identifying rare single nucleotide and copy number variants may offer valuable insights into the underlying pathophysiology.

We conducted a systematic review of all genetic abnormalities reported with catatonia and performed a gene-set enrichment analysis. Our systematic literature search for relevant articles published through July 15, 2024, using combinations of “catatonia,” “catatonic syndrome,” “genetic,” and “genes” in PubMed, yielded 317 articles. Of these, 94 were included, covering 374 cases of catatonia and 78 distinct genetic abnormalities.

This review discusses the clinical presentation of catatonia for each genetic disorder, the treatment strategies, and the putative underlying mechanisms.

The review highlights that catatonia underpinned by genetic abnormalities presents specific clinical and treatment-response features. Therefore, we propose genetic testing guidelines for catatonia and advocate for systematically investigating catatonia in several genetic diseases. Regarding the pathophysiology of catatonia, the gene ontology of biological processes reveals significant enrichment of variants in synaptic and post-synaptic regulatory genes, particularly within GABAergic neurons, reinforcing the implication of the excitatory/inhibitory imbalance. Finally, genetic variants are enriched in microglial cells, highlighting the role of brain inflammation in triggering catatonia. This comprehensive insight could pave the way for more effective management strategies for this condition.

Clinical high risk for psychosis (CHR) is often managed with antipsychotic medications, but their effects on neurocognitive performance and clinical outcomes remain insufficiently explored. This study investigates the association between aripiprazole and olanzapine use and cognitive and clinical outcomes in CHR individuals, compared to those receiving no antipsychotic treatment.

A retrospective analysis was conducted on 127 participants from the Shanghai At Risk for Psychosis (SHARP) cohort, categorized into three groups: aripiprazole, olanzapine, and no antipsychotic treatment. Neurocognitive performance was evaluated using the MATRICS Consensus Cognitive Battery (MCCB), while clinical symptoms were assessed through the Structured Interview for Prodromal Syndromes (SIPS) at baseline, 8 weeks, and one year.

The non-medicated group demonstrated greater improvements in cognitive performance, clinical symptoms, and functional outcomes compared to the medicated groups. Among the antipsychotic groups, aripiprazole was associated with better visual learning outcomes than olanzapine. Improvements in neurocognition correlated significantly with clinical symptom relief and overall functional gains at follow-up assessments.

These findings suggest potential associations between antipsychotic use and cognitive outcomes in CHR populations while recognizing that observed differences may reflect baseline illness severity rather than medication effects alone. Aripiprazole may offer specific advantages over olanzapine, underscoring the importance of individualized risk-benefit evaluations in treatment planning. Randomized controlled trials are needed to establish causality.

There is increasing emphasis on reducing the use and improving the safety of mechanical restraint (MR) in psychiatric settings, and on improving the quality of evidence for outcomes. To date, however, a systematic appraisal of evidence has been lacking.

We included studies of adults (aged 18–65) admitted to inpatient psychiatric settings. We included primary randomised or observational studies from 1990 onwards that reported patterns of MR and/or outcomes associated with MR, and qualitative studies referring to an index admission or MR episode. We presented prevalence data only for studies from 2010 onwards. The risk of bias was assessed using an adapted checklist for randomised/observational studies and the Newcastle-Ottawa scale for interventional studies.

We included 83 articles on 73 studies from 1990–2022, from 22 countries. Twenty-six studies, from 11 countries, 2010 onwards, presented data from on proportions of patients/admissions affected by MR. There was wide variation in prevalence (<1–51%). This appeared to be mostly due to variations in standard protocols between countries and regions, which dictated use compared to other restrictive practices such as seclusion. Indications for MR were typically broad (violence/aggression, danger to self or property). The most consistently associated factors were the early phase of admission, male sex, and younger age. Ward and staff factors were inconsistently examined. There was limited reporting of patient experience or positive effects.

MR remains widely practiced in psychiatric settings internationally, with considerable variation in rates, but few high-quality studies of outcomes. There was a notable lack of studies investigating different types of restraint, indications, clinical factors associated with use, the impact of ethnicity and language, and evidence for outcomes. Studies examining these factors are crucial areas for future research. In limiting the use of MR, some ward-level interventions show promise, however, wider contextual factors are often overlooked.

Schizophrenia is a multifactorial disorder with a range of risk factors. Dysregulation in the systems involved in the stress response is a key component of its pathophysiology. Individuals at risk of developing schizophrenia exhibit hyperreactivity to stress and altered cognitive performance, both known as vulnerability markers. This study aims to determine whether stimulation of the prefrontal cortex can reduce reactivity to stress in unaffected siblings of patients with schizophrenia.

In a randomized, sham-controlled trial, 27 participants were assigned to receive either active (n = 14) or sham (n = 13) transcranial direct current stimulation (tDCS) over the prefrontal cortex for 30 min during exposure to an acute stressor. The stress response was measured biologically, via salivary cortisol levels, and cognitively, through a reality monitoring task, which serves as an intermediate cognitive vulnerability marker.

In contrast to the sham condition, active stimulation significantly reduced cortisol release in response to stress (F(9,216) = 1.972; p = 0.04) and prevented stress-induced impairment in reality monitoring (F(1,23) = 9.954; p = 0.004).

These findings suggest that tDCS should be a promising tool for reducing stress-induced biological and cognitive reactivity in a population at risk of schizophrenia.

Studies examining age-stratified risk factors for suicide among individuals with bipolar disorder in different stages of life are scant, possibly because of the insufficient number of suicide cases.

This study investigated suicide mortality rates and risk profiles of suicide mortality stratified by five age groups in individuals with bipolar disorder.

This study identified patients with a diagnosis of bipolar disorder between January 1, 2000, and December 31, 2021, from Taiwan’s National Health Insurance Research Database. The study population comprised 45,211 inpatients diagnosed with bipolar disorder, with 1,370 suicide cases during the study period. We calculated the standardized mortality ratio (SMR) of the bipolar cohort relative to the general population. In the age-stratified nested case–control study, risk set sampling was performed to match 1 suicide case with 10 living controls by age, sex, and the year of first diagnosis. The age-stratified risk associated with demographic characteristics, psychiatric and physical comorbidities was estimated using multivariable conditional logistic regression.

The highest SMR (47.0) for suicide was observed in individuals with bipolar disorder aged <30 years. SMR decreased with age; patients aged >60 years had an SMR of 9.5. Among those younger than 40 years, a higher percentage of unemployment was noted among suicide cases than among controls. A significantly increased risk of the depressive phase of bipolar disorder was noted shortly before suicide mortality among patients with bipolar disorder in all age groups. Drug-induced and alcohol-induced mental disorders were associated with suicide and were highly prevalent in patients aged <30 years. Other forms of heart disease were identified in patients aged <40 years, and pneumonia was detected in the 50–59 years age group.

These findings aid the development of health-care intervention strategies for preventing suicide among patients with bipolar disorder in various stages of life.

The diagnosis of ADHD in adults is on the rise. Applying the ADHD diagnosis, which originally was described in children, to adults has involved a “subjectivization” of some of the diagnostic criteria, i.e., some behavioral features (signs) in children have become experiences (symptoms) in adults. These issues raise the question of how ADHD is best diagnosed in adults? Thus, we examined how ADHD is diagnosed in adults in research.

A review of how ADHD is diagnosed in adults in randomized controlled studies (RCTs).

We include 292 RCTs. We found substantial variation and no consensus about the diagnostic method. More than half of the studies did not seem to include an assessment of general psychopathology, and only in 35% of studies was the ADHD diagnosis allocated by psychiatrists or psychologist. More than half of the studies included patients with psychiatric comorbidity.

These findings raise concerns about the validity of the ADHD diagnosis in many of the included RCTs. It is worrying that securing a reasonably accurate diagnosis is not prioritized in more than half of the studies. If neither clinicians nor researchers can rely on the basic fact the patients in scientific studies diagnostically resemble the patients they are facing, scientific studies risk losing their clinical relevance. Since RCTs can lead to changes in clinical practice, they must be conducted carefully. To advance research on adult ADHD, the quality of the diagnostic assessment must be prioritized, requiring comprehensive differential diagnosis by a skilled psychiatrist or psychologist.

Unhealthy lifestyle behaviors are prevalent among people with mental illness (MI), affecting their physical and mental health. Most research has focused on the isolated effects of lifestyle behaviors, leaving the interconnectedness between these behaviors and health outcomes unexplored. This study aimed to examine these relationships and identify the most strongly connected lifestyle behavior or health outcome within a network.

We conducted a cross-sectional study with 423 inpatients with MI, receiving care as usual. Lifestyle behaviors, physical and mental health outcomes were assessed through questionnaires and routine data. A Gaussian Graphical Model was estimated, and strength centrality was calculated to identify the most influential nodes.

Mean age was 55.5 years, 42% were female, and 41% were diagnosed with schizophrenia. Psychological and physical quality of life (QoL), nighttime sleep problems, and overall sleep quality were the most strongly connected nodes. Sleep was strongly associated with physical QoL. Furthermore, there were negative associations between healthy food intake and cholesterol ratio, and positive associations between daily doses of antipsychotics and length of hospital stay. Node strength was stable (CS(cor = 0.7) = 0.75). No clear pattern emerged among other lifestyle behaviors and health outcomes.

This study offers insights into the interrelatedness of lifestyle behaviors and health outcomes. Addressing sleep problems could enhance QoL and potentially influence other health outcomes. Psychological and physical QoL were also strongly associated, emphasizing the importance of perceived well-being in health outcomes. Future research could explore causal pathways to identify treatment targets to improve care.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that often persists into adulthood, significantly impacting daily functioning and quality of life. Sex differences influence ADHD presentation, with females experiencing delayed diagnosis and distinct patterns of severity and comorbidities. Exploring these differences is essential for improving diagnostic accuracy and developing tailored interventions. This study examines ADHD severity, psychiatric comorbidities, and functional impairment by ADHD subtype and sex.

This population-based study included 900 adults diagnosed with ADHD. ADHD severity, comorbidities, and functional outcomes were assessed using validated tools. Bivariate analyses and General Linear Models (GLMs) were applied to examine sex- and subtype-specific effects and their interactions.

Females exhibited greater ADHD severity (p < 0.001), higher levels of depression (p = 0.003) and anxiety (p < 0.001), lower substance use (p < 0.001), poorer functioning (p = 0.039), and greater disability (p = 0.001) than males. No significant sex differences were found in ADHD subtype distribution or age of symptom onset; however, females were diagnosed with ADHD later than males (p < 0.001). The combined ADHD subtype was associated with greater clinical severity, higher levels of depression, anxiety, and impulsive symptoms, increased substance use, and greater disability. A significant interaction between sex and subtype was observed only for disability, with females in the combined subtype exhibiting the most pronounced impairment.

ADHD presents differently across sexes and subtypes, with specific interactions influencing disability. These findings emphasize the importance of considering sex and ADHD subtype independently to enhance diagnostic accuracy and develop targeted treatment strategies.